Polygenic Risk, Early Adverse Life Events And Depression In The Ipsych Cohort

Background Major depressive disorder (MDD) is moderately genetic, with population-based heritability estimates of 30-40% and SNP-based heritability estimates of 20-25%. However, a large proportion of risk for MDD is attributable to the environment. Early adverse life events (EALEs), such as the death of a parent, are well-established risk factors for MDD. Candidate gene studies indicate that EALEs interact with single genes to influence MDD risk. However, mounting evidence suggests that the underlying genetic architecture of MDD is polygenic. To date, only two studies have examined whether polygenic risk (PR) interacts with early adversity to predict MDD. Peyrot et al. (2014) found in the NESDA study that the effect of PR on MDD was stronger among individuals with a history of childhood trauma. Mullins et al. (2016) found the opposite: among people with moderate/severe trauma, the log odds of MDD decreased as PR increased. The goal of this study is to evaluate the extent to which EALEs interact with PR to predict MDD in the Danish iPSYCH cohort. The iPSYCH cohort contains 88,764 individuals, including 24,693 MDD cases, making this by far the largest study on the topic to date. Methods The iPSYCH cohort has a case-cohort design, containing individuals randomly sampled from the population of people born in Denmark between May 1, 1981-Dec 31, 2005, along with additional psychiatric cases identified from the Danish Central Psychiatric Research Register. DNA was extracted from dried blood spots and amplified in triplicate. Individuals were genotyped using the PSYCH chip. In this study, we will use data from controls and cases with an MDD diagnosis (ICD-10 codes F32, F33). EALEs, including death of a parent, death of a sibling, parental hospitalization, parental imprisonment, parental unemployment, parental divorce/separation, foster care and abuse, will be assessed using information from other Danish nationwide registers. EALEs will be operationalized as a weighted count variable of the number of events experienced by each individual before the age of 15. PR scores will be calculated using the PGC2 MDD results (not including the iPSYCH sample) as the training dataset (Purcell, 2009). Statistical analyses will be conducted using Cox Proportional Hazards Models, with weights to account for the case-cohort design (Self u0026 Prentice, 1988). Results The PR scores which will be used in this study are currently being finalized. We anticipate that this process will be finished in August, 2016, which will give us over two months to conduct the analyses and prepare the results for presentation at the WCPG conference. Discussion Pending finalization of results.